Technology

Technology plays a central role in achieving the Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure), SDG 4 (Quality Education), SDG 3 (Good Health and Well-being), and SDG 13 (Climate Action). The transformative power of technology can accelerate progress towards all the SDGs by driving economic growth, reducing inequalities, enhancing access to basic services, and promoting sustainability.

Under SDG 9, technology, particularly in terms of Information and Communication Technology (ICT), is a key enabler of industrial innovation and infrastructure development. ICT has the potential to drive economic growth by enhancing productivity, creating jobs, and fostering entrepreneurship. Moreover, it can contribute to making industries more sustainable by facilitating the transition towards smart manufacturing and circular economy models.

Regarding SDG 4, technology can greatly enhance access to quality education. Digital technologies, including e-learning platforms, can break down barriers to education, such as geographical distance, socio-economic status, and physical disabilities. They can also enrich the learning process by enabling personalized, student-centered learning experiences.

In the context of SDG 3, technology has a profound impact on health outcomes. Medical technologies, from simple devices like thermometers to complex systems like MRI machines, have revolutionized healthcare delivery. Furthermore, digital health technologies, such as telemedicine and mobile health apps, can enhance access to health services, improve patient outcomes, and reduce healthcare costs.

For SDG 13, technology offers powerful tools for mitigating and adapting to climate change. Renewable energy technologies can help to reduce greenhouse gas emissions, while climate information services can enhance resilience to climate impacts. Furthermore, digital technologies can facilitate the monitoring and reporting of climate actions, contributing to greater transparency and accountability.

However, the benefits of technology are not automatic, and there are significant challenges to overcome, including the digital divide, cybersecurity threats, and ethical issues related to privacy and data ownership. Thus, policy interventions and multi-stakeholder partnerships are needed to ensure that technology serves as a catalyst for sustainable development and does not exacerbate inequalities.

Elsevier, Current Opinion in Green and Sustainable Chemistry, Volume 31, October 2021
Global warming and climate change caused by an ever-increasing accumulation of atmospheric CO2 are reaching alarming levels. In order to address this issue, significant research effort has been dedicated to the development of carbon capture processes for sequestration or utilization of CO2. Current technologies rely on energy-intensive temperature- or pressure-swing of CO2 sorbents, limiting the economic feasibility of the process. Herein, we review recent advances in electrochemically mediated CO2 capture and release.
In the run up to COP26, the United Nations Climate Change conference, RELX’s Global Head of Corporate Responsibility, Dr Márcia Balisciano, talks to Prof Trevor Letcher, Prof Carolina Arlota & Prof Hirdan Costa about the energy transition required to meet the Paris Agreement.
Short-term exposures to indoor air contaminants can cause adverse health impacts and warrant a need for real-time measurements. The most common indoor pollutants are carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), total volatile organic compounds (TVOCs), and particulate matter with a diameter of less than 2.5 μm (PM2.5). Several low-cost monitors for indoor air quality are commercially available; however, few of them are accurately tested. A stable, easy to use, and reproducible platform was developed in this paper.
This Research Paper supports SDGs 5 and 10 by applying machine learning techniques to understand gender-based violence in contexts with low prevalence data, offering insight into factors associated with non-marital sexual violence in India.
Read the story behind eyeWitness to Atrocities, an app developed by the International Bar Association (IBA) and LexisNexis Legal & Professional, which helps bring war criminals to justice. It’s the first app that collects, verifies, catalogues and protects images so that they can be used as evidence in a court of law while helping protect the individuals who have been brave enough to take the photos or videos.
This chapter advances UN SDG goals 11 and 13 by examining how the development of clean technologies can reduce potential environmental and human health hazards associated with the production of nanotechnology products.
Elsevier and the International Solar Energy Society (ISES) are pleased to announce the third biennial Renewable Transformation Challenge. If you have an innovative proposal which contributes to the goal of transitioning to 100% renewable energy, submit your application for a chance to win €20,000.
To show the importance of climate action and to celebrate the more than 5-year collaboration between the Elsevier Chemistry journals department and the Elsevier Foundation, we have compiled this special issue, highlighting top chemistry content related to SDG 13 and providing information on past winners of the Green & Sustainable Chemistry Challenge.

The chemical industry needs to significantly decrease carbon dioxide (CO2) emissions in order to meet the 2050 carbon neutrality goal. Utilization of CO2 as a chemical feedstock for bulk products is a promising way to mitigate industrial emissions; however, CO2-based manufacturing is currently not competitive with the established petrochemical methods and its deployment requires creation of a new value chain.

Based on the joint HCPMMP parcellation method we developed before, which divides the cortical brain into 360 regions, the concept of ordered core features (OCF) is first proposed to reveal the functional brain connectivity relationship among different cohorts of Alzheimer's disease (AD), late mild cognitive impairment (LMCI), early mild cognitive impairment (EMCI) and healthy controls (HC). A set of core network features that change significantly under the specifically progressive relationship were extracted and used as supervised machine learning classifiers.

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